Taming Big Data with MapReduce & Hadoop

Analyze Large Amounts of Data with Today's Top Big Data Technologies

Big data is hot, and data management and analytics skills are your ticket to a fast-growing, lucrative career. This course will quickly teach you two technologies fundamental to big data: MapReduce and Hadoop. Learn and master the art of framing data analysis problems as MapReduce problems with over 10 hands-on examples. Write, analyze, and run real code along with the instructor– both on your own system, and in the cloud using Amazon's Elastic MapReduce service. By course's end, you'll have a solid grasp of data management concepts.

Frank Kane spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis.
For more details on this course and instructor, click here. This course is hosted by StackSkills, the premier eLearning destination for discovering top-shelf courses on everything from coding—to business—to fitness, and beyond!

Details & Requirements

Length of time users can access this course: lifetime

Access options: web streaming, mobile streaming

Certification of completion not included

Redemption deadline: redeem your code within 30 days of purchase

Experience level required: all levels

Compatibility

Internet required

Course Outline

Introduction

Introduction

Getting Started

Installing Enthought Canopy

Installing MRJob

Downloading the MovieLens Data Set

Run Your First MapReduce Job

Understanding MapReduce

MapReduce Basic Concepts

Walkthrough of Rating Histogram Code

Understanding How MapReduce Scales / Distributed Computing

Average Friends by Age Example: Part 1 (3:04)

Average Friends by Age Example: Part 2

Minimum Temperature By Location Example

Maximum Temperature By Location Example

Word Frequency in a Book Example

Making the Word Frequency Mapper Better with Regular Expressions

Sorting the Word Frequency Results Using Multi-Stage MapReduce Jobs

Activity: Design a Mapper and Reducer for Total Spent by Customer (2:54)

Projects in Hadoop and Big Data: Learn by Building Apps

Master One of the Most Important Big Data Technologies by Building Real Projects

Hadoop is perhaps the most important big data framework in existence, used by major data-driven companies around the globe. Hadoop and its associated technologies allow companies to manage huge amounts of data and make business decisions based on analytics surrounding that data. This course will take you from big data zero to hero, teaching you how to build Hadoop solutions that will solve real world problems - and qualify you for many high-paying jobs.

Eduonix creates and distributes high-quality technology training content. Their team of industry professionals has been training manpower for more than a decade. They aim to teach technology the way it is used in the industry and professional world. They have a professional team of trainers for technologies ranging from Mobility, Web and Enterprise, and Database and Server Administration.

Details & Requirements

Length of time users can access this course: lifetime

Access options: web streaming, mobile streaming

Certification of completion not included

Redemption deadline: redeem your code within 30 days of purchase

Experience level required: intermediate

Compatibility

Internet required

Course Outline

Introduction

Introduction

Add Value to Existing Data with Mapreduce

Introduction to the Project

Build and Run the Basic Code

Understanding the Code

Dependencies and packages

Hadoop Analytics and NoSQL

Introduction to Hadoop Analytics

Introduction to NoSQL Database

Solution Architecture

Installing the Solution

Kafka Streaming with Yarn and Zookeeper

Introduction to Kafka Yarn and Zookeeper

Code Structure

Creating Kafka Streams

Yarn Job with Samza

Real Time Stream processing with Apache Kafka and Apache Storm

Real Time Streaming

Hortonbox Virtual Machine

Running in Cluster Mode

Submitting the Storm Jar

Big Data Applications for the Healthcare Industry with Apache Sqoop and Apache S

Introduction to the Project

Introduction to HDDAccess

Sqoop, Hive and Solr

Hive Usage

Log collection and analytics with the Hadoop Distributed File System using Apach

Learn Hadoop, MapReduce and Big Data from Scratch

Master Big Data Ecosystems & Implementation to Further Your IT Professional Dream

Have you ever wondered how major companies, universities, and organizations manage and process all the data they've collected over time? Well, the answer is Big Data, and people who can work with it are in huge demand. In this course you'll cover the MapReduce algorithm and its most popular implementation, Apache Hadoop. Throughout this comprehensive course, you'll learn essential Big Data terminology, MapReduce concepts, advanced Hadoop development, and gain a complete understanding of the Hadoop ecosystem so you can become a big time IT professional.

Learn the differences between Hadoop Distributed File System vs. Google File System

Eduonix creates and distributes high-quality technology training content. Their team of industry professionals has been training manpower for more than a decade. They aim to teach technology the way it is used in the industry and professional world. They have a professional team of trainers for technologies ranging from Mobility, Web and Enterprise, and Database and Server Administration.

Website - www.eduonix.com

For more details on this course and instructor, click here. This course is hosted by StackSkills, the premier eLearning destination for discovering top-shelf courses on everything from coding—to business—to fitness, and beyond!

Introduction to Hadoop

Get Familiar with One of the Top Big Data Frameworks In the World

Hadoop is one of the most commonly used Big Data frameworks, supporting the processing of large data sets in a distributed computing environment. This tool is becoming more and more essential to big business as the world becomes more data-driven. In this introduction, you'll cover the individual components of Hadoop in detail and get a higher level picture of how they interact with one another. It's an excellent first step towards mastering Big Data processes.

Loonycorn is comprised of four individuals--Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi and Navdeep Singh--who have honed their tech expertises at Google and Flipkart. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

Advanced MapReduce in Hadoop

Perform Advanced Big Data Functions with Hadoop

Take your Hadoop skills to a whole new level by exploring its features for controlling and customizing MapReduce to a very granular level. Covering advanced topics like building inverted indexes for search engines, generating bigrams, combining multiple jobs, and much more, this course will push your skills towards a professional level.

Use MapReduce to build an inverted index for search engines & generate bigrams from text

Chain multiple MapReduce jobs together

Write your own customized partitioner

Sort a large amount of data by sampling input files

Loonycorn is comprised of four individuals--Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi and Navdeep Singh--who have honed their tech expertises at Google and Flipkart. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

Database Operations via Hadoop and MapReduce

Analyze Data More Efficiently by Learning MapReduce's Parallels to SQL

Analyzing data is an essential to making informed business decisions, and most data analysts use SQL queries to get the answers they're looking for. In this course, you'll learn how to map constructs in SQL to corresponding design patterns for MapReduce jobs, allowing you to understand how these two programs can be leveraged together to simplify data problems.

Access 49 lectures & 1.5 hours of content 24/7

Master the art of "thinking parallel" to break tasks into MapReduce transformations

Use Hadoop & MapReduce to implement a SQL query like operations

Work through SQL constructs such as select, where, group by, & more w/ their corresponding MapReduce jobs in Hadoop

Loonycorn is comprised of four individuals--Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi and Navdeep Singh--who have honed their tech expertises at Google and Flipkart. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

Recommendation Systems Via Hadoop And MapReduce

Build a Social Network Friend Recommendation Service from Scratch

You see recommendation algorithms all the time, whether you realize it or not. Whether it's Amazon recommending a product, Facebook recommending a friend, Netflix, a new TV show, recommendation systems are a big part of internet life. This is done by collaborative filtering, something you can perform through MapReduce with data collected in Hadoop. In this course, you'll learn how to do it.

Access 4 lectures & 1 hour of content 24/7

Master the art of "thinking parallel" to break tasks into MapReduce transformations

Use Hadoop & MapReduce to implement a recommendations algorithm

Recommend friends on a social networking site using a MapReduce collaborative filtering algorithm

Loonycorn is comprised of four individuals--Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi and Navdeep Singh--who have honed their tech expertises at Google and Flipkart. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

Details & Requirements

Length of time users can access this course: lifetime

Access options: web streaming, mobile streaming

Certification of completion not included

Redemption deadline: redeem your code within 30 days of purchase

Experience level required: all levels

IDE like IntelliJ or Eclipse required (free to download)

Compatibility

Internet required

Course Outline

Introduction

You, this course and Us (1:11)

Recommendation Systems using Collaborative Filtering

Introduction to Collaborative Filtering (7:25)

Friend recommendations using chained MR jobs (17:15)

Get common friends for every pair of users - the first MapReduce (14:50)

Top 10 friend recommendation for every user - the second MapReduce (13:46)

K-Means Clustering via Hadoop And MapReduce

Decipher Big Data Sets Through a Prominent Machine Learning Algorithm

Data, especially in enterprise, will often expand at a rapid scale. Hadoop excels at compiling and organizing this data, however, to do anything meaningful with it, you may need to run machine learning algorithms to decipher patterns. In this course, you'll learn one such algorithm, the K-Means clustering algorithm, and how to use MapReduce to implement it in Hadoop.

Access 7 lectures & 1.5 hours of content 24/7

Master the art of "thinking parallel" to break tasks into MapReduce transformations

Use Hadoop & MapReduce to implement the K-Means clustering algorithm

Convert algorithms into MapReduce patterns

Loonycorn is comprised of four individuals--Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi and Navdeep Singh--who have honed their tech expertises at Google and Flipkart. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.